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Modeling formulation and a new heuristic for the railroad blocking problem

APPLIED MATHEMATICAL MODELLING 2018年 56卷 304-324页

作者： Hasany, Reza Mohammad Shafahi, Yousef Sharif Univ Technol Dept Civil Engn Azadi AvePOB 11155-8639 Tehran Iran

The railroad blocking problem is an important issue at the tactical level of railroad freight transportation. This problem consists of determining paths between the origins and destinations of each shipment to minimize the operating and user costs while satisfying the railroad supply and demand restrictions. A mixed-integer program (MIP) is developed to find the optimal paths, and a new heuristic is developed to solve the proposed model. This heuristic decomposes the model into two sub-problems of manageable size and then provides feasible solutions. We discuss the performance of the proposed heuristic for a set of instances with up to 90 stations. A comparison with the CPLEX MIP solver shows that the heuristic gives the exact solution for 10 out of 15 instances. For the remaining instances, the heuristic obtained solutions within a tolerance of 0.03-0.84%. Furthermore, compared with the CPLEX MIP solver, the heuristic reduced the run time by an average of 85% for all 15 instances. Finally, we present the computational results of the heuristic applied to Iranian railroads. (C) 2017 Elsevier Inc. All rights reserved.

关键词： Railroad blocking problem Decomposition method mixed-integer programming Heuristic

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Exact methods for the quay crane scheduling problem when tasks are modeled at the single container level

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COMPUTERS & OPERATIONS RESEARCH 2018年 99卷 218-233页

作者： Msakni, Mohamed Kais Diabat, Ali Rabadi, Ghaith Al-Salem, Mohamed Kotachi, Mariam Qatar Univ Dept Mech & Ind Engn Doha Qatar New York Univ Abu Dhabi Div Engn Abu Dhabi 129188 U Arab Emirates NYU Tandon Sch Engn Dept Civil & Urban Engn Brooklyn NY 11201 USA Old Dominion Univ Dept Engn Management & Syst Engn Norfolk VA 23529 USA

The scheduling of quay cranes (QCs) to minimize the handling time of a berthed vessel is one of the most important operations in container terminals as it impacts the terminal's overall productivity. In this paper, we propose two exact methods to solve the quay crane scheduling problem (QCSP) where a task is defined as handling a single container and subject to different technical constraints including QCs' safety margin, non-crossing, initial position, and nonzero traveling time. The first method is based on two versions of a compact mixed-integer programming formulation that can solve large problem instances using a general purpose solver. The second is a combination of some constraints of the proposed mathematical model and the binary search algorithm to reduce the CPU time, and solve more efficiently large-sized problems. Unlike existing studies, the computational study demonstrates that both methods can reach optimal solutions for large-sized instances and validates their dominance compared to an exact model proposed in the literature which finds solutions only for small problems. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Scheduling Container terminals Quay crane scheduling problem mixed-integer programming

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The Weighted Fair Sequences Problem

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COMPUTERS & OPERATIONS RESEARCH 2018年 91卷 121-131页

作者： Pessoa, Bruno Jefferson de S. Aloise, Daniel Cabral, Lucidio A. F. Univ Fed Paraiba UFPB Ctr Informat Joao Pessoa Paraiba Brazil Ecole Polytech Comp Engn Dept Montreal PQ Canada

Scheduling problems on which constraints are imposed with regard to the temporal distances between successive executions of the same task have numerous applications, ranging from task scheduling in real-time systems to automobile production on a mixed-model assembly line. This paper introduces a new NP-hard optimization problem belonging to this class of problems, namely the Weighted Fair Sequences Problem (WFSP). We present a mathematical formulation for the WFSP based on mixed-integer linear programming (MILP) as well as a series of cuts to improve its resolution via exact methods. Finally, we propose a heuristic solution method that works with much less variables of the WFSP formulation. The reported computational experiments show that, for a given time horizon, the proposed MILP-based heuristic increases the size of WFSP instances that can be tackled in practice. Moreover, its results should be considered as optimal whether a presented conjecture on the WFSP problem is proved true in the future. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Scheduling Fair sequences mixed-integer programming

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MIP formulations for an application of project scheduling in human resource management

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FLEXIBLE SERVICES AND MANUFACTURING JOURNAL 2018年第4期30卷 609-639页

作者： Rihm, Tom Trautmann, Norbert Zimmermann, Adrian Univ Bern Dept Business Adm Bern Switzerland Univ Bern Quantitat Methods Business Adm Bern Switzerland

In the literature, various discrete-time and continuous-time mixed-integer linear programming (MIP) formulations for project scheduling problems have been proposed. The performance of these formulations has been analyzed based on generic test instances. The objective of this study is to analyze the performance of discrete-time and continuous-time MIP formulations for a real-life application of project scheduling in human resource management. We consider the problem of scheduling assessment centers. In an assessment center, candidates for job positions perform different tasks while being observed and evaluated by assessors. Because these assessors are highly qualified and expensive personnel, the duration of the assessment center should be minimized. Complex rules for assigning assessors to candidates distinguish this problem from other scheduling problems discussed in the literature. We develop two discrete-time and three continuous-time MIP formulations, and we present problem-specific lower bounds. In a comparative study, we analyze the performance of the five MIP formulations on four real-life instances and a set of 240 instances derived from real-life data. The results indicate that good or optimal solutions are obtained for all instances within short computational time. In particular, one of the real-life instances is solved to optimality. Surprisingly, the continuous-time formulations outperform the discrete-time formulations in terms of solution quality.

关键词： OR in the service industries Human resource management Project scheduling mixed-integer programming Comparative analysis

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Convex Models for Optimal Utility-Based Distributed Generation Allocation in Radial Distribution Systems

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IEEE SYSTEMS JOURNAL 2018年第4期12卷 3497-3508页

作者： Akbari, Mohammad Amin Aghaei, Jamshid Barani, Mostafa Niknam, Taher Ghavidel, Sahand Farahmand, Hossein Korpas, Magnus Li, Li Shiraz Univ Technol Dept Elect & Elect Engn Shiraz *** Iran Norwegian Univ Sci & Technol Dept Elect Power Engn N-7491 Trondheim Norway Univ Technol Fac Engn & Informat Technol Sydney NSW 2007 Australia

This paper introduces various models for optimal and maximal utility-based distributed generation penetration in the radial distribution systems. Several problems with different probabilistic indices as objective functions constrained by power flow equations, distributed generation penetration, voltage, and thermal limits are proposed to obtain the optimal penetration of distributed generations on rural distribution networks. There are tradeoffs between interests and risks that the distribution network operators or distribution companies may be willing to take on. Thus, to have an effective method for maximal allocation of distributed generations, new indices are proposed, and the problems are formulated as a risk-constrained optimization model. The obtained problems have mixed-integer nonlinear programming and nonconvex forms because of nonlinearity and nonconvexity of the optimal power flow(OPF) equations and indices, leading to computationally nondeterministic polynomial-time-hard problems. Accordingly, in this paper, convex relaxations of OPF are introduced instead of the conventional nonlinear equations. Efficient linear equivalents of the objective function and constraints are introduced to reduce the computational burden. Test results of the proposed models on a radial distribution system are presented and discussed.

关键词： Convex models distributed generation (DG) energy losses mixed-integer programming quadratic programming risk constraints voltage profile

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Hybrid robust, stochastic and possibilistic programming for closed-loop supply chain network design

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COMPUTERS & INDUSTRIAL ENGINEERING 2018年 123卷 220-231页

作者： Dehghan, Ehsan Nikabadi, Mohsen Shafiei Amiri, Maghsoud Jabbarzadeh, Armin Semnan Univ Fac Econ & Management Dept Ind Management Semnan Iran Allameh Tabatabai Univ Fac Management & Accounting Dept Ind Management Tehran Iran IUST Dept Ind Engn Tehran Iran

The main goal of this study is to address gap in the area of Closed-loop Supply Chain Network Design (CLSCND) under the hybrid uncertain conditions. To do this, a multi-product and multi-period model is developed in an edible oil supply chain. Since the proposed model includes two kinds of uncertain parameters, the scenario- and fuzzy-based parameters, a novel Robust Stochastic-Possibilistic programming (RSPP) are proposed to cope with uncertain parameters, based on the Me measure. Furthermore, the performance of the RSPP model is reviewed, its weaknesses and strengths are studied, and it is compared with the other models. Finally, the usefulness and applicability of the RSPP model are tested by the real industrial case study.

关键词： mixed-integer programming Edible oil supply chain Closed loop supply chain network design Robust possibilistic programming Stochastic programming

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A novel boundary swarm optimization method for reliability redundancy allocation problems

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2019年 192卷

作者： Yeh, Wei-Chang Natl Tsing Hua Univ Dept Ind Engn & Engn Management Integrat & Collaborat Lab Hsinchu Taiwan

A new methodology called boundary simplified swarm optimization (BSO) is proposed by integrating a novel self-boundary search (SBS) and a two-variable update mechanism (UM2) to improve simplified swarm optimization (SSO) in solving mixed-integer programing problems that include both discrete and continuous variables. To balance the exploration and exploitation ability, the proposed SBS is implemented to update the current best solution (called gBest) based on the boundary conditions and analytical calculations to enhance the exploitation ability of gBest, the UM2 updates the solutions (called non-gBest) that are not gBest to fix the over-exploration of the SSO, in which all variables need to update without exploiting the information of the neighborhood area. The performance of the proposed BSO is ascertained by comparing the results with existing algorithms using four reliability redundancy allocation benchmark problems in the existing literature.

关键词： Reliability redundancy allocation problems Update mechanism Simplified swarm optimization mixed-integer programming

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Aircraft routing with generalized maintenance constraints

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2018年 80卷 111-122页

作者： Safaei, Nima Jardine, Andrew K. S. Scotiabank Data Sci & Analyt 40 King St W Toronto ON M5H 1H1 Canada Univ Toronto Dept Mech & Ind Engn 5 Kings Coll Rd Toronto ON M5S 3G8 Canada

The literature on aircraft maintenance routing generally ignores the full range of maintenance requirements by only considering the most frequent maintenance type. The range of maintenance types and variety of individual aircraft's ages and utilization rates means the maintenance demand for each aircraft differs from one period to another, thus complicating aircraft routing decisions. This study proposes a new formulation of the aircraft maintenance routing problem in which maintenance requirements are built as generalized capacity constraints, ensuring sufficient maintenance opportunities are available within the planned routes to satisfy the maintenance demands of individual aircraft. Our new approach suggests minimizing maintenance misalignment using an interactive mechanism between aircraft routing and maintenance planning decisions. The computational results using real datasets reveal continuous reduction and convergence in maintenance misalignment through the proposed interactive mechanism. The lack of an effective interaction between the abovementioned decisions significantly increases the maintenance misalignment costs. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Aircraft routing Capacity constraints Maintenance mixed-integer programming

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Least cost influence propagation in (social) networks

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MATHEMATICAL programming 2018年第1期170卷 293-325页

作者： Fischetti, Matteo Kahr, Michael Leitner, Markus Monaci, Michele Ruthmair, Mario Univ Padua DEI Padua Italy Univ Vienna Dept Stat & Operat Res Vienna Austria Univ Bologna DEI Bologna Italy

Influence maximization problems aim to identify key players in (social) networks and are typically motivated from viral marketing. In this work, we introduce and study the Generalized Least Cost Influence Problem (GLCIP) that generalizes many previously considered problem variants and allows to overcome some of their limitations. A formulation that is based on the concept of activation functions is proposed together with strengthening inequalities. Exact and heuristic solution methods are developed and compared for the new problem. Our computational results also show that our approaches outperform the state-of-the-art on relevant, special cases of the GLCIP.

关键词： Influence maximization mixed-integer programming Social network analysis

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Joint planning of service engineers and spare parts

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2018年第1期271卷 97-108页

作者： Sleptchenko, Andrei Al Hanbali, Ahmad Zijm, Henk Khalifa Univ Sci & Technol Coll Engn Dept Ind & Syst Engn POB 127788 Abu Dhabi U Arab Emirates King Fahd Univ Petr & Minerals Coll Comp Sci & Engn Syst Engn Dept Dhahran 31261 Saudi Arabia Univ Twente Fac Behav Management & Social Sci Dept Ind Engn & Business Informat Syst POB 217 NL-7500 AE Enschede Netherlands

We analyze the joint optimization of spare parts inventories and workforce allocation in a single-site maintenance system. In this system, for each failure, a service engineer with a necessary replacement part has to be allocated. If one of the required resources is not available, the incoming failure request is routed to an external provider, such as a centralized repair facility or a sub-contractor. We study multiple failure types (related to failing components) with exponentially distributed inter-failure times. The system repair times and the replenishment times of the spare parts inventory are also exponentially distributed. The inventory replenishment is done according to a Base-Stock policy. The objective is to minimize the total system cost consisting of annual holding costs of the spare parts and the service engineers, and incidental outsourcing costs. For the joint optimization of the resources, we propose a mixed-integer programming (MIP) formulation using the balance equations of the Markov Chain representation of the system. Furthermore, we provide a simple and efficient heuristic that produces close-to-optimal (<0.3% difference) results, for solving larger instances. Using the proposed optimization methods and real-life data, we analyze the optimal balance between the costs of the resources and the outsourcing costs and show how the outsourcing rates and the total costs behave for different system parameters. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Maintenance Spare Parts Service engineers Markov process mixed-integer programming

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